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Proceedings of the International Conference on Health Informatics and Medical Application Technology最新文献

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A Gait Analysis Tool Based on Machine Learning to Support the Rehabilitation Strategy of Post-stroke Patients 基于机器学习的步态分析工具支持脑卒中后患者康复策略
N. Balletti, G. Laudato, R. Oliveto
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引用次数: 0
On a Real Real-Time Wearable Human Activity Recognition System 一种实时可穿戴人体活动识别系统
Hui Liu, Tingting Xue, Tanja Schultz
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引用次数: 17
A Correlation Network Model for Analyzing Mobility Data in Depression Related Studies 抑郁症相关研究中流动性数据分析的相关网络模型
Rama Krishna Thelagathoti, Hesham H. Ali
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引用次数: 0
Benchmarking the BRATECA Clinical Data Collection for Prediction Tasks 对预测任务的BRATECA临床数据收集进行基准测试
B. Consoli, Renata Vieira, Rafael Heitor Bordini
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引用次数: 0
The Use of Machine Learning to Predict Hospitalization of Covid-19: A Case Study in the State of Minas Gerais - Brazil 使用机器学习预测Covid-19住院治疗:巴西米纳斯吉拉斯州的案例研究
Gerda Graciela Rodrigues de Oliveira, Cristiane Nobre
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引用次数: 0
How Different Elements of Audio Affect the Word Error Rate of Transcripts in Automated Medical Reporting 不同的音频元素如何影响自动医疗报告的文字错误率
Emma Kwint, Anna Zoet, Katsiaryna Labunets, S. Brinkkemper
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引用次数: 0
Extended Head Pose Estimation on Synthesized Avatars for Determining the Severity of Cervical Dystonia 基于合成头像的扩展头姿估计用于判断颈肌张力障碍的严重程度
Roland Stenger, Sebastian Löns, Feline Hamami, Nele Sophie Brügge, T. Bäumer, Sebastian J. F. Fudickar
: We present an extended head pose estimation algorithm, which is trained exclusively on synthesized human avatars. Having five degrees of freedom to describe such head poses, this task can be regarded as being more complex than predicting the absolute rotation only with three degrees of freedom, which is commonly known as head pose estimation. Due to the lack of labeled data sets containing such complex head poses, we created a data set, consisting of renderings of avatars. With this extension, we take a step towards an algorithm that can make a qualitative assessment of cervical dystonia. Its symptomatic consists of an involuntary twisted head posture, which can be described by those five degrees of freedom. We trained an EfficientNetB2 and evaluated the results with the mean absolute error (MAE). Such estimation is possible, but the performance works differently well for the five degrees of freedom, with an MAE between 1.71° and 6.55°. By visually randomizing the domain of the avatars, the gap between real subject photos and the simulated ones might tend to be smaller and enables our algorithm being used on real photos in the future, while being trained on renderings only.
我们提出了一种扩展的头部姿态估计算法,该算法专门针对合成的人类化身进行训练。由于有五个自由度来描述这样的头部姿态,这个任务可以被认为比只有三个自由度的绝对旋转预测更为复杂,这通常被称为头部姿态估计。由于缺乏包含如此复杂头部姿势的标记数据集,我们创建了一个由化身渲染组成的数据集。有了这个扩展,我们采取了一步的算法,可以使宫颈肌张力障碍的定性评估。它的症状包括不自觉的头部扭曲姿势,这可以用这五个自由度来描述。我们训练了一个有效率的netb2,并用平均绝对误差(MAE)评估结果。这样的估计是可能的,但是对于五个自由度的性能表现不同,MAE在1.71°和6.55°之间。通过视觉上随机化头像的域,真实主体照片和模拟照片之间的差距可能会变小,从而使我们的算法能够在未来用于真实照片,而只在渲染图上进行训练。
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引用次数: 0
Integration of a Deep Learning-Based Module for the Quantification of Imaging Features into the Filling-in Process of the Radiological Structured Report 将基于深度学习的影像特征量化模块集成到放射学结构化报告填充过程中
Camilla Scapicchio, E. Ballante, F. Brero, R. F. Cabini, A. Chincarini, M. Fantacci, Silvia Figini, A. Lascialfari, Francesca Lizzi, I. Postuma, A. Retico
,
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引用次数: 0
Digital Therapeutics for Healthy Longevity: A Roadmap 健康长寿的数字疗法:路线图
Tim Leistner, T. Kowatsch
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引用次数: 0
Deep Learning Assisted Plus Disease Screening of Retinal Image of Infants 深度学习辅助婴儿视网膜图像的疾病筛查
Vijay Kumar, Vatsal Agrawal, S. Azad, Kolin Paul
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引用次数: 1
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Proceedings of the International Conference on Health Informatics and Medical Application Technology
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